问题
I have a single series of values (i.e. one column of data), and I would like to create a plot with the range of data values on the x-axis and the frequency that each value appears in the data set on the y-axis.
What I would like is very close to a Kernel Density Plot:
# Kernel Density Plot
d <- density(mtcars$mpg) # returns the density data
plot(d) # plots the results
and Frequency distribution in R on stackoverflow.
However, I would like frequency (as opposed to density) on the y-axis.
Specifically, I'm working with network degree distributions, and would like a double-log scale with open, circular points, i.e. this image.
I've done research into related resources and questions, but haven't found what I wanted:
Cookbook for R's Plotting distributions is close to what I want, but not precisely. I'd like to replace the y-axis in its density curve example with "count" as it is defined in the histogram examples.
The ecdf() function in R (i.e. this question) may be what I want, but I'd like the observed frequency, and not a normalized value between 0 and 1, on the y-axis.
This question is related to frequency distributions, but I'd like points, not bars.
EDIT:
The data is a standard power-law distribution, i.e.
dat <- c(rep(1, 1000), rep(10, 100), rep(100, 10), 100)
回答1:
If you have discrete values for observations and want to make a plot with points on the log scale, then
dat <- c(rep(1, 1000), rep(10, 100), rep(100, 10), 100)
dd<-aggregate(rep.int(1, length(dat))~dat, FUN=sum)
names(dd)<-c("val","freq")
plot(freq~val, dd, log="xy")
might be what you are after.
回答2:
The integral of a density is approximately 1 so multiplying the density$y estimate by the number of values should give you something on the scale of a frequency. If you want a "true" frequency then you should use a histogram:
d <- density(mtcars$mpg)
d$y <- d$y * length(mtcars$mpg) ; plot(d)
This is a histogram with breaks that are 1 unit each:
hist(mtcars$mpg,
breaks=trunc(min(mtcars$mpg)):(1+trunc(max(mtcars$mpg))), add=TRUE)
So this is the superposed comparison:
d <- density(mtcars$mpg)
d$y <- d$y * length(mtcars$mpg) ; plot(d, ylim=c(0,4) )
hist(mtcars$mpg, breaks=trunc(min(mtcars$mpg)):(1+trunc(max(mtcars$mpg))), add=TRUE)
You'll want to look at the density page where the default density bandwidth choice is criticized and alternatives offered. f you use the adjust parameter you might see a closer (smoothed correspondence to the histogram
来源：https://stackoverflow.com/questions/24399492/plot-frequency-distribution-of-one-column-data-in-r